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Biomedical subjects

Bob Kemp

Publications and source records attributed to Bob Kemp.

5 recordsLinked to original sources

An E-health solution for automatic sleep classification according to Rechtschaffen and Kales: validation study of the Somnolyzer 24 x 7 utilizing the Siesta database.

To date, the only standard for the classification of sleep-EEG recordings that has found worldwide acceptance are the rules published in 1968 by Rechtschaffen and Kales. Even though several attempts have been made to automate the classification process, so far no method has been published that has proven its validity in a study including a sufficiently large number of controls and patients of all adult age ranges. The present paper describes the development and optimization of an automatic classification system that is based on one central EEG channel, two EOG channels and one chin EMG channel. It adheres to the decision rules for visual scoring as closely as possible and includes a structured quality control procedure by a human expert. The final system (Somnolyzer 24 x 7) consists of a raw data quality check, a feature extraction algorithm (density and intensity of sleep/wake-related patterns such as sleep spindles, delta waves, SEMs and REMs), a feature matrix plausibility check, a classifier designed as an expert system, a rule-based smoothing procedure for the start and the end of stages REM, and finally a statistical comparison to age- and sex-matched normal healthy controls (Siesta Spot Report). The expert system considers different prior probabilities of stage changes depending on the preceding sleep stage, the occurrence of a movement arousal and the position of the epoch within the NREM/REM sleep cycles. Moreover, results obtained with and without using the chin EMG signal are combined. The Siesta polysomnographic database (590 recordings in both normal healthy subjects aged 20-95 years and patients suffering from organic or nonorganic sleep disorders) was split into two halves, which were randomly assigned to a training and a validation set, respectively. The final validation revealed an overall epoch-by-epoch agreement of 80% (Cohen's kappa: 0.72) between the Somnolyzer 24 x 7 and the human expert scoring, as compared with an inter-rater reliability of 77% (Cohen's kappa: 0.68) between two human experts scoring the same dataset. Two Somnolyzer 24 x 7 analyses (including a structured quality control by two human experts) revealed an inter-rater reliability close to 1 (Cohen's kappa: 0.991), which confirmed that the variability induced by the quality control procedure, whereby approximately 1% of the epochs (in 9.5% of the recordings) are changed, can definitely be neglected. Thus, the validation study proved the high reliability and validity of the Somnolyzer 24 x 7 and demonstrated its applicability in clinical routine and sleep studies.

Adult↗

SignalML from an EDF+ perspective.

Both SignalML and EDF+ offer a solution for the incompatibility between different data storage formats in biomedicine. This article discusses the SignalML approach from an EDF+ point of view.

Data Interpretation, Statistical↗

Easy listening to sleep recordings: tools and examples.

BACKGROUND AND PURPOSE: To specify a simple conversion of neurophysiological signals contained in sleep recordings into standard audio files and to illustrate how our cerebral audio processor can then detect specific signal characteristics. METHODS: A software package (freely accessible from the Internet) has been developed that converts signals from standard EDF (or EDF+) format to standard audio (WAV) format, a process usually called audification. The software has been applied to sleep EEG, EOG and ECG. The software is easy to apply. RESULTS: A wide range of audified signals is described, stressing the analogy with familiar sounds. Audio properties of EEG in different sleep stages, EOG, ECG and respiration signals are discussed. Auditive presentation of the signals invokes brain processes that differ essentially from the commonly applied visual interpretation, including physiological frequency analysis. CONCLUSIONS: Such auditive interpretation may complement the visual one. The widespread use of EDF+ and multimedia computers makes such audification simple and straightforward.

Adult↗

Epidemiology of restless legs in The Netherlands.

The prevalence of restless legs syndrome (RLS) in various regions in the world has been estimated between 2.5 and 29%. For The Netherlands these figures are not known. Our observational and cross-sectional study was performed to estimate the prevalence of RLS in The Netherlands. A cross-sectional survey by postal questionnaire was carried out through a general practice in a small town in which one general practice serves 93% of the population. All men and women aged 50 years and older were invited to fill out the questionnaire on leg movements, quality of sleep and daytime symptoms. A total of 1485 (88.2%) persons returned their questionnaire and 1437 (85.4%) patients answered the questions on leg movements. A total of 102 (7.1%) inhabitants answered positively to the questions on leg movements and probably have RLS. The prevalence was higher in women and increased with age. People who complain of RLS have significantly more complaints of disturbances in initiating and maintaining sleep, sleepiness, tiredness during the day and less refreshing sleep. RLS is common in The Netherlands with an estimated prevalence of 7.1% in the population over 50 years of age.

Adult↗

European data format 'plus' (EDF+), an EDF alike standard format for the exchange of physiological data.

The European data format (EDF) is a widely accepted standard for exchange of electroencephalogram and polysomnogram data between different equipment and labs. But it hardly accommodates other investigations. EDF+ is a more flexible but still simple format which is compatible to EDF except that an EDF+ file may contain interrupted recordings. Also, EDF+ supports time-stamped annotations for the storage of events such as text annotations, stimuli, averaged signals, electrocardiogram parameters, apnoeas and so on. When compared to EDF, EDF+ can not only store annotations but also electromyography, evoked potentials, electroneurography, electrocardiography and many more types of investigations. Further improvements over EDF include the use of standard electrode names. EDF+ is so much like EDF that existing EDF viewers still display the signals in EDF+ files. Software development is limited mainly to implementing the annotations. EDF+ offers a format for a wide range of neurophysiological investigations which can become a standard within a few years.

Data Interpretation, Statistical↗